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相关概念视频

Quantifying Work02:30

Quantifying Work

As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an organic...
What are Estimates?01:06

What are Estimates?

It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such as the mean,...
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
Signal Flow Graphs01:18

Signal Flow Graphs

Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...

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相关实验视频

Updated: Jun 25, 2026

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
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从加密视频会议流量中估计QOE.

Michael Sidorov1, Raz Birman1, Ofer Hadar1

  • 1School of Electrical and Computer Engineering, Ben Gurion University of the Negev, Be'er Sheba 8410501, Israel.

Sensors (Basel, Switzerland)
|February 26, 2025
PubMed
概括

这项研究预测了使用加密流量进行视频会议的体验质量 (QoE). 机器学习模型准确地估计了关键指标,如每秒 (FPS) 和分辨率 (R),改进了互联网安全分析.

科学领域:

  • 计算机科学 计算机科学
  • 网络工程 网络工程
  • 信息安全 信息安全

背景情况:

  • 互联网安全依赖于流量加密,这阻碍了对视频交付优化和体验质量 (QoE) 估计等应用程序的分析.
  • 现有的QoE预测模型主要集中在清晰文本流量上,并且经常提供低分辨率的分类预测,使视频会议 (VC) 领域未得到充分探索.

研究的目的:

  • 解决视频会议 (VC) 应用程序中加密流量的 QoE 评估中的挑战.
  • 开发准确,连续的风险投资者QOE预测,超越广泛的类别.
  • 分析加密的流量数据以改善QOE估计.

主要方法:

  • 对包含Zoom会话的大数据集的分析.
  • 培训和评估五种经典机器学习 (ML) 模型.
  • 开发和培训两个定制深度神经网络 (DNN).
  • 预测三个关键的QOE指标:每秒 (FPS),分辨率 (R) 和自然性图像质量评估器 (NIQE).
  • 使用十倍交叉验证技术进行可靠的模型评估.

主要成果:

  • 在FPS预测中实现了8.27%的平均错误率.
  • 实现了分辨率 (R) 预测的7.56%的平均错误率.
关键词:
深度学习是一种深度学习.通过加密的流量来实现.机器学习是机器学习.经验的质量体验的质量.通过视频会议进行视频会议.

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  • 对于自然性图像质量评估器 (NIQE) 预测的平均错误率为2.08%.
  • 结论:

    • 开发的模型表明,在VC应用程序中对加密流量进行QOE评估方面取得了重大进展.
    • 即使使用加密的视频会议数据,也可以实现精确,连续的QOE预测.
    • 这项研究为增强网络管理和视频会议服务用户体验提供了基础.